Python - 计算 Pandas DataFrame 中列的标准差
要计算标准偏差，请使用std()Pandas的方法。首先，导入所需的Pandas库-
import pandas as pd
现在，创建一个包含两列的DataFrame-
dataFrame1 = pd.DataFrame(
{
"Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'],
"Units": [100, 150, 110, 80, 110, 90] }
)使用std()-查找“单位”列值的标准偏差-
print"Standard Deviation of Units column from DataFrame1 = ",dataFrame1['Units'].std()
以同样的方式，我们计算了第二个DataFrame的标准偏差。
示例
以下是完整的代码-
#
#Python-计算PandasDataFrame列值的标准差
#
import pandas as pd
#创建DataFrame1
dataFrame1 = pd.DataFrame(
{
"Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'],
"Units": [100, 150, 110, 80, 110, 90]
}
)
print"DataFrame1 ...\n",dataFrame1
# Finding Standard Deviation of "Units" column values
print"Standard Deviation of Units column from DataFrame1 = ",dataFrame1['Units'].std()
#创建DataFrame2
dataFrame2 = pd.DataFrame(
{
"Product": ['TV', 'PenDrive', 'HeadPhone', 'EarPhone', 'HDD', 'SSD'],
"Price": [8000, 500, 3000, 1500, 3000, 4000]
}
)
print"\nDataFrame2 ...\n",dataFrame2
# Finding Standard Deviation of "Price" column values
print"Standard Deviation of Price column from DataFrame2 = ",dataFrame2['Price'].std()输出结果这将产生以下输出-
DataFrame1 ...
Car Units
0 BMW 100
1 Lexus 150
2 Audi 110
3 Tesla 80
4 Bentley 110
5 Jaguar 90
Standard Deviation of Units column from DataFrame1 = 24.2212028328
DataFrame2 ...
Price Product
0 8000 TV
1 500 PenDrive
2 3000 HeadPhone
3 1500 EarPhone
4 3000 HDD
5 4000 SSD
Standard Deviation of Price column from DataFrame2 = 2601.28173535